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Van Dyken PC, Yang K, Faria AV, Sawa A, MacKinley M, Khan AR, Palaniyappan L. Stable White Matter Structure in the First Three Years After Psychosis Onset. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2025; 5:100472. [PMID: 40231305 PMCID: PMC11994302 DOI: 10.1016/j.bpsgos.2025.100472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Revised: 02/08/2025] [Accepted: 02/11/2025] [Indexed: 04/16/2025] Open
Abstract
Background White matter alterations observed using diffusion weighted imaging have become a hallmark of chronic schizophrenia, but it is unclear when these changes arise over the course of the disease. Nearly all studies reported to date have been cross-sectional, so despite their large sample sizes, they cannot determine whether changes accumulate as a degenerative process or patients with preexisting white matter damage are predisposed to more chronic forms of schizophrenia. Methods We examined 160 scans comprising 2 years of annual follow-up data from 42 control participants and 28 patients with schizophrenia recruited in the first 2 years since their diagnosis, totaling 2 to 3 scans per participant. We also examined 6-month follow-up data obtained from an ultra-high field (7T) scanner (68 scans; n = 19 patients with first-episode schizophrenia, n = 15 control participants) as a validation dataset. A longitudinal model was used to compare the trajectory of diffusion tensor parameters in patients and control participants. Results Positive and negative symptom scores were correlated with diffusion parameters using region of interest-based approaches. No longitudinal differences between patients and control participants were observed for any diffusion tensor imaging parameter in either dataset. However, we did observe consistent associations between white matter alterations and negative symptoms in both datasets. Conclusions White matter does not appear to be susceptible to schizophrenia-linked degeneration in the early stages of disease, but preexisting pathology may be linked to disease severity.
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Affiliation(s)
- Peter C. Van Dyken
- Neuroscience Graduate Program, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Andreia V. Faria
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Akira Sawa
- Departments of Psychiatry, Neuroscience, Biomedical Engineering, Pharmacology, and Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Michael MacKinley
- Lawson Health Research Institute, London Health Sciences Centre, London, Ontario, Canada
| | - Ali R. Khan
- Robarts Research Institute, Western University, London, Ontario, Canada
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Lena Palaniyappan
- Robarts Research Institute, Western University, London, Ontario, Canada
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
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Nenadić I, Mosebach J, Schmitt S, Meller T, Stein F, Brosch K, Ringwald K, Pfarr JK, Meinert S, Lemke H, Waltemate L, Thiel K, Opel N, Repple J, Grotegerd D, Steinsträter O, Sommer J, Hahn T, Jansen A, Dannlowski U, Krug A, Kircher T. Fronto-Thalamic Structural Connectivity Associated With Schizotypy, a Psychosis Risk Phenotype, in Nonclinical Subjects. Schizophr Bull 2025; 51:S137-S148. [PMID: 40037831 PMCID: PMC11879573 DOI: 10.1093/schbul/sbad143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/06/2025]
Abstract
BACKGROUND AND HYPOTHESIS Schizotypy is a risk phenotype for the psychosis spectrum and pilot studies suggest a biological continuum underlying this phenotype across health and disease. It is unclear whether this biological continuum might include brain structural associations in networks altered in schizophrenia spectrum disorders, such as the fronto-thalamo-striatal system or nodes of the default mode network, such as the precuneus. STUDY DESIGN In this study, we analyze a large multi-center cohort of 673 nonclinical subjects phenotyped for schizotypal traits (using the Schizotypal Personality Questionnaire-Brief version) using tract-based spatial statistics of diffusion tensor imaging data, as well as voxel-based morphometry (VBM) analysis of regional brain volumes and gyrification analysis of early neurodevelopmental markers of cortical folding on T1-weighted MRI. STUDY RESULTS We identify significant (P < .05 family-wise error corrected) associations of schizotypy with major fiber tract fractional anisotropy: positive (cognitive-perceptual) schizotypy correlated negatively with the left anterior thalamic radiation (a principal thalamo-frontal projection), left uncinate fasciculus and cingulum, while negative (interpersonal) schizotypy correlated positively with left anterior thalamic radiation, cingulum, and the anterior corpus callosum, and disorganized schizotypy correlated negatively with right cingulum, and superior and inferior longitudinal fasciculi. VBM analyses showed a negative correlation of gray matter with negative schizotypy in the left cerebellum, while gyrification in the inferior parietal cortex correlated positively with negative (interpersonal) schizotypy. CONCLUSIONS These findings pave the way for a neural network conceptualization of schizotypy as a psychosis proneness trait across the general population, showing associations with fronto-subcortical and frontotemporal systems as structural substrates of this risk phenotype.
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Affiliation(s)
- Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Johannes Mosebach
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Kai Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lena Waltemate
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
- German Center for Mental Health (DZPG), Jena, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Goethe University Frankfurt, University Hospital, Frankfurt, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Olaf Steinsträter
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
- Core-Facility BrainImaging, School of Medicine, Philipps-Universität Marburg, Marburg, Germany
| | - Jens Sommer
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
- Core-Facility BrainImaging, School of Medicine, Philipps-Universität Marburg, Marburg, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
- Core-Facility BrainImaging, School of Medicine, Philipps-Universität Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
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Çabuk T, Şahin Çevik D, Çakmak IB, Yılmaz Kafalı H, Şenol B, Avcı H, Karlı Oğuz K, Toulopoulou T. Analyzing language ability in first-episode psychosis and their unaffected siblings: A diffusion tensor imaging tract-based spatial statistics analysis study. J Psychiatr Res 2024; 179:229-237. [PMID: 39321521 DOI: 10.1016/j.jpsychires.2024.09.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 08/16/2024] [Accepted: 09/19/2024] [Indexed: 09/27/2024]
Abstract
Schizophrenia (SZ) is a highly heritable mental disorder, and language dysfunctions play a crucial role in diagnosing it. Although language-related symptoms such as disorganized speech were predicted by the polygenic risk for SZ which emphasized the common genetic liability for the disease, few studies investigated possible white matter integrity abnormalities in the language-related tracts in those at familial high-risk for SZ. Also, their results are not consistent. In this current study, we examined possible aberrations in language-related white matter tracts in patients with first-episode psychosis (FEP, N = 20), their siblings (SIB, N = 20), and healthy controls (CON, N = 20) by applying whole-brain Tract-Based Spatial Statistics and region-of-interest analyses. We also assessed language ability by Thought and Language Index (TLI) using Thematic Apperception Test (TAT) pictures and verbal fluency to see whether the scores of these language tests would predict the differences in these tracts. We found significant alterations in language-related tracts such as inferior longitudinal fasciculus (ILF) and uncinate fasciculus (UF) among three groups and between SIB and CON. We also proved partly their relationship with the language test as indicated by the significant correlation detected between TLI Impoverished thought/language sub-scale and ILF. We could not find any difference between FEP and CON. These results showed that the abnormalities, especially in the ILF and UF, could be important pathophysiological vulnerability indexes of schizophrenia. Further studies are required to understand better the role of language as a possible endophenotype in schizophrenia with larger samples.
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Affiliation(s)
- Tuğçe Çabuk
- Department of Psychology, National Magnetic Resonance Research Center (UMRAM) & Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey; Department of Psychology, Başkent University, Ankara, Turkey
| | - Didenur Şahin Çevik
- Department of Neuroscience, National Magnetic Resonance Research Center (UMRAM) & Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey
| | | | - Helin Yılmaz Kafalı
- Department of Psychology, Fevziye Schools Foundations Işık University, İstanbul, Turkey
| | - Bedirhan Şenol
- Department of Psychiatry, Bilkent Şehir Hospital, Ankara, Turkey
| | - Hanife Avcı
- Department of Biostatistics, Hacettepe University, Ankara, Turkey
| | - Kader Karlı Oğuz
- Department of Radiology, University of California Medical Center, Sacramento, USA
| | - Timothea Toulopoulou
- Department of Psychology, National Magnetic Resonance Research Center (UMRAM) & Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey; Department of Neuroscience, National Magnetic Resonance Research Center (UMRAM) & Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey; 1st Department of Psychiatry, National and Kapodistrian University of Athens, Athens, Greece; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA.
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Shi H, Zhang Y, Yang Y, Zhang H, Li W, Zhong Z, Lv L. Serum S100B protein and white matter changes in schizophrenia before and after medication. Brain Res Bull 2024; 210:110927. [PMID: 38485004 DOI: 10.1016/j.brainresbull.2024.110927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 03/11/2024] [Indexed: 03/23/2024]
Abstract
Schizophrenia patients have abnormalities in white matter (WM) integrity in brain regions. S100B has been shown to be a marker protein for glial cells. The atypical antipsychotics have neuroprotective effects on the brain. It is not clear whether antipsychotics can induce S100B changes and improve symptoms by protecting oligodendrocytes. To investigate WM and S100B changes and associations and determine the effect of quetiapine on WM and S100B in schizophrenia patients, we determined serum S100B levels with solid phase immunochromatography and fractional anisotropy(FA)values of 36 patients and 40 healthy controls. Patients exhibited significantly higher serum concentrations of S100B and decreased FA values in left postcentral,right superior frontal,right thalamus, and left inferior occipital gyrus, while higher in right temporal cortex WM compared with healthy controls. Following treatment with quetiapine, patients had decreased S100B and higher FA values in right cerebellum,right superior frontal,right thalamus, and left parietal cortex,and decreased FA values in right temporal cortex WM compared with pre-treatment values. Furthermore, S100B were negatively correlated with PANSS positive scores and positively correlated with FA values in the left postcentral cortex. In addition,the percentage change in FA values in the right temporal cortex was positively correlated with the percentage change in the S100B, percentage reduction in PANSS scores, and percentage reduction in PANSS-positive scores. Our findings demonstrated abnormalities in S100B and WM microstructure in patients with schizophrenia. These abnormalities may be partly reversed by quetiapine treatment.
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Affiliation(s)
- Han Shi
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China; International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yan Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China; International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China; International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Haisan Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Wenqiang Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China; International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Zhaoxi Zhong
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China; International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China.
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China; International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China.
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Moghaddam HS, Parsaei M, Taghavizanjani F, Cattarinussi G, Aarabi MH, Sambataro F. White matter alterations in affective and non-affective early psychosis: A diffusion MRI study. J Affect Disord 2024; 351:615-623. [PMID: 38290585 DOI: 10.1016/j.jad.2024.01.238] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 01/06/2024] [Accepted: 01/26/2024] [Indexed: 02/01/2024]
Abstract
BACKGROUND The early years after the onset of psychotic disorders, known as "early psychosis" (EP) are critical to determining the path of psychosis trajectory. We used a Diffusion Magnetic Resonance Imaging (DMRI) connectometry approach to assess the microstructural changes of white matter (WM) associated with EP. METHODS We used the Human Connectome Project in Early Psychosis (HCP-EP) dataset to collect DMRI data from patients with EP. The imaging data were processed in the Montreal Neuroimaging Initiative space and transformed into quantitative anisotropy (QA). The QA value was translated into the WM connectivity of each tract and used in the subsequent analysis. RESULTS 121 patients with EP (94 non-affective/27 affective) and 56 healthy controls were recruited. EP was associated with increased QA in the body and tapetum of corpus callosum (CC) and decreased QA in the bilateral cerebellum, and middle cerebellar peduncle. Compared to non-affective psychosis, affective psychosis showed increased QA in the bilateral cerebellum and vermis and decreased QA in the forceps minor, body of CC, right cingulum, and bilateral inferior fronto-occipital fasciculus. Furthermore, QA changes in several WM tracts were correlated with positive and negative symptom scale scores. LIMITATIONS DMRI intrinsic limitations, limited sample size, and neurobiological effects of psychotropic treatment. CONCLUSIONS EP is associated with alterations in WM connectivity primarily in the CC and cerebellar regions. Also, affective and non-affective psychosis have distinct alterations in WM connectivity. These results can be used for the early diagnosis and differentiation of psychotic disorders.
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Affiliation(s)
| | - Mohammadamin Parsaei
- Maternal, Fetal & Neonatal Research Center, Family Health Research Institute, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Fateme Taghavizanjani
- Psychiatric Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Mohammad Hadi Aarabi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy.
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Grosu C, Klauser P, Dwir D, Khadimallah I, Alemán-Gómez Y, Laaboub N, Piras M, Fournier M, Preisig M, Conus P, Draganski B, Eap CB. Associations between antipsychotics-induced weight gain and brain networks of impulsivity. Transl Psychiatry 2024; 14:162. [PMID: 38531873 DOI: 10.1038/s41398-024-02881-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 03/13/2024] [Accepted: 03/15/2024] [Indexed: 03/28/2024] Open
Abstract
Given the unpredictable rapid onset and ubiquitous consequences of weight gain induced by antipsychotics, there is a pressing need to get insights into the underlying processes at the brain system level that will allow stratification of "at risk" patients. The pathophysiological hypothesis at hand is focused on brain networks governing impulsivity that are modulated by neuro-inflammatory processes. To this aim, we investigated brain anatomy and functional connectivity in patients with early psychosis (median age: 23 years, IQR = 21-27) using anthropometric data and magnetic resonance imaging acquired one month to one year after initiation of AP medication. Our analyses included 19 patients with high and rapid weight gain (i.e., ≥5% from baseline weight after one month) and 23 patients with low weight gain (i.e., <5% from baseline weight after one month). We replicated our analyses in young (26 years, IQR = 22-33, N = 102) and middle-aged (56 years, IQR = 51-62, N = 875) healthy individuals from the general population. In early psychosis patients, higher weight gain was associated with poor impulse control score (β = 1.35; P = 0.03). Here, the observed brain differences comprised nodes of impulsivity networks - reduced frontal lobe grey matter volume (Pcorrected = 0.007) and higher striatal volume (Pcorrected = 0.048) paralleled by disruption of fronto-striatal functional connectivity (R = -0.32; P = 0.04). Weight gain was associated with the inflammatory biomarker plasminogen activator inhibitor-1 (β = 4.9, P = 0.002). There was no significant association between increased BMI or weight gain and brain anatomy characteristics in both cohorts of young and middle-aged healthy individuals. Our findings support the notion of weight gain in treated psychotic patients associated with poor impulse control, impulsivity-related brain networks and chronic inflammation.
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Affiliation(s)
- Claire Grosu
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland.
| | - Paul Klauser
- Service of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Daniella Dwir
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Ines Khadimallah
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Yasser Alemán-Gómez
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
- Connectomics Lab, Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Nermine Laaboub
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Marianna Piras
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Margot Fournier
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Martin Preisig
- Psychiatric Epidemiology and Psychopathology Research Center, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Philippe Conus
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, Prilly, Switzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neuroscience - Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Neurology Department, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Chin B Eap
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland.
- School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.
- Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva and University of Lausanne, Lausanne, Switzerland.
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Tabata K, Son S, Miyata J, Toriumi K, Miyashita M, Suzuki K, Itokawa M, Takahashi H, Murai T, Arai M. Association of homocysteine with white matter dysconnectivity in schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:39. [PMID: 38509166 PMCID: PMC10954654 DOI: 10.1038/s41537-024-00458-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 03/11/2024] [Indexed: 03/22/2024]
Abstract
Several studies have shown white matter (WM) dysconnectivity in people with schizophrenia (SZ). However, the underlying mechanism remains unclear. We investigated the relationship between plasma homocysteine (Hcy) levels and WM microstructure in people with SZ using diffusion tensor imaging (DTI). Fifty-three people with SZ and 83 healthy controls (HC) were included in this retrospective observational study. Tract-Based Spatial Statistics (TBSS) were used to evaluate group differences in WM microstructure. A significant negative correlation between plasma Hcy levels and WM microstructural disruption was noted in the SZ group (Spearman's ρ = -.330, P = 0.016) but not in the HC group (Spearman's ρ = .041, P = 0.712). These results suggest that increased Hcy may be associated with WM dysconnectivity in SZ, and the interaction between Hcy and WM dysconnectivity could be a potential mechanism of the pathophysiology of SZ. Further, longitudinal studies are required to investigate whether high Hcy levels subsequently cause WM microstructural disruption in people with SZ.
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Grants
- 19K17061 Ministry of Education, Culture, Sports, Science and Technology (MEXT)
- 18H02749 Ministry of Education, Culture, Sports, Science and Technology (MEXT)
- 18H05130 Ministry of Education, Culture, Sports, Science and Technology (MEXT)
- 20H05064 Ministry of Education, Culture, Sports, Science and Technology (MEXT)
- 23H04979 Ministry of Education, Culture, Sports, Science and Technology (MEXT)
- 21H02849 Ministry of Education, Culture, Sports, Science and Technology (MEXT)
- 21H05173 Ministry of Education, Culture, Sports, Science and Technology (MEXT)
- 23H02844 Ministry of Education, Culture, Sports, Science and Technology (MEXT)
- JP18dm0307008 Japan Agency for Medical Research and Development (AMED)
- JP21uk1024002 Japan Agency for Medical Research and Development (AMED)
- JPMJCR22P3 MEXT | JST | Core Research for Evolutional Science and Technology (CREST)
- The Novartis Pharma Research Grant; SENSHIN Medical Research Foundation; SUZUKEN Memorial Foundation; the Takeda Science Foundation.
- the Brain/MINDS Beyond program (23dm0307008) from the Japan Agency for Medical Research
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Affiliation(s)
- Koichi Tabata
- Schizophrenia Research Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Shuraku Son
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
| | - Jun Miyata
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Kazuya Toriumi
- Schizophrenia Research Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Mitsuhiro Miyashita
- Unit for Mental Health Promotion, Research Center for Social Science & Medicine, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Kazuhiro Suzuki
- Schizophrenia Research Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
- Department of Psychiatry, Shinshu University School of Medicine, Matsumoto, Japan
| | - Masanari Itokawa
- Schizophrenia Research Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
- Department of Psychiatry, Tokyo Metropolitan Matsuzawa Hospital, Tokyo, Japan
| | - Hidehiko Takahashi
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
- Center for Brain Integration Research, Tokyo Medical and Dental University, Tokyo, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Makoto Arai
- Schizophrenia Research Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
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Zeng Q, Yu J, Hu Q, Yin K, Li Q, Huang J, Xie L, Wang J, Zhang C, Wang J, Zhang J, Feng Y. Investigation into white matter microstructure differences in visual training by using an automated fiber tract subclassification segmentation quantification method. Neurosci Lett 2024; 821:137574. [PMID: 38036084 DOI: 10.1016/j.neulet.2023.137574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/25/2023] [Accepted: 11/27/2023] [Indexed: 12/02/2023]
Abstract
Visual training has emerged as a useful framework for investigating training-related brain plasticity, a highly complex task involving the interaction of visual orientation, attention, reasoning, and cognitive functions. However, the effects of long-term visual training on microstructural changes within white matter (WM) is poorly understood. Therefore, a set of visual training programs was designed, and automated fiber tract subclassification segmentation quantification based on diffusion magnetic resonance imaging was performed to obtain the anatomical changes in the brains of visual trainees. First, 40 healthy matched participants were randomly assigned to the training group or the control group. The training group underwent 10 consecutive weeks of visual training. Then, the fiber tracts of the subjects were automatically identified and further classified into fiber clusters to determine the differences between the two groups on a detailed scale. Next, each fiber cluster was divided into segments that can analyze specific areas of a fiber cluster. Lastly, the diffusion metrics of the two groups were comparatively analyzed to delineate the effects of visual training on WM microstructure. Our results showed that there were significant differences in the fiber clusters of the cingulate bundle, thalamus frontal, uncinate fasciculus, and corpus callosum between the training group compared and the control group. In addition, the training group exhibited lower mean fractional anisotropy, higher mean diffusivity and radial diffusivity than the control group. Therefore, the long-term cognitive activities, such as visual training, may systematically influence the WM properties of cognition, attention, memory, and processing speed.
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Affiliation(s)
- Qingrun Zeng
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China
| | - Jiangli Yu
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China
| | - Qiming Hu
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China
| | - Kuiying Yin
- Nanjing Research Institute of Electronic Technology, Nanjing 210012, China
| | - Qixue Li
- Nanjing Research Institute of Electronic Technology, Nanjing 210012, China
| | - Jiahao Huang
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China
| | - Lei Xie
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China
| | - Jingqiang Wang
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China
| | - Chengzhe Zhang
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China
| | - Jiafeng Wang
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China
| | - Jiawei Zhang
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China
| | - Yuanjing Feng
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China; Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310023, China.
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Chen Y, Liu S, Zhang B, Zhao G, Zhang Z, Li S, Li H, Yu X, Deng H, Cao H. Baseline symptom-related white matter tracts predict individualized treatment response to 12-week antipsychotic monotherapies in first-episode schizophrenia. Transl Psychiatry 2024; 14:23. [PMID: 38218952 PMCID: PMC10787827 DOI: 10.1038/s41398-023-02714-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 12/06/2023] [Accepted: 12/13/2023] [Indexed: 01/15/2024] Open
Abstract
There is significant heterogeneity in individual responses to antipsychotic drugs, but there is no reliable predictor of antipsychotics response in first-episode psychosis. This study aimed to investigate whether psychotic symptom-related alterations in fractional anisotropy (FA) and mean diffusivity (MD) of white matter (WM) at the early stage of the disorder may aid in the individualized prediction of drug response. Sixty-eight first-episode patients underwent baseline structural MRI scans and were subsequently randomized to receive a single atypical antipsychotic throughout the first 12 weeks. Clinical symptoms were evaluated using the eight "core symptoms" selected from the Positive and Negative Syndrome Scale (PANSS-8). Follow-up assessments were conducted at the 4th, 8th, and 12th weeks by trained psychiatrists. LASSO regression model and cross-validation were conducted to examine the performance of baseline symptom-related alterations FA and MD of WM in the prediction of individualized treatment outcome. Fifty patients completed both clinical follow-up assessments by the 8th and 12th weeks. 30 patients were classified as responders, and 20 patients were classified as nonresponders. At baseline, the altered diffusion properties of fiber tracts in the anterior thalamic radiation, corticospinal tract, callosum forceps minor, longitudinal fasciculi (ILF), inferior frontal-occipital fasciculi (IFOF) and superior longitudinal fasciculus (SLF) were related to the severity of symptoms. These abnormal fiber tracts, especially the ILF, IFOF, and SLF, significantly predicted the response to antipsychotic treatment at the individual level (AUC = 0.828, P < 0.001). These findings demonstrate that early microstructural WM changes contribute to the pathophysiology of psychosis and may serve as meaningful individualized predictors of response to antipsychotics.
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Affiliation(s)
- Ying Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Hope Recovery and Rehabilitation Center, West China Hospital of Sichuan University, Chengdu, China
| | - Shanming Liu
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Bo Zhang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Gaofeng Zhao
- Shandong Daizhuang Hospital, Jining, Shangdong, China
| | - Zhuoqiu Zhang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Shuiying Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Haiming Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Hong Deng
- Hope Recovery and Rehabilitation Center, West China Hospital of Sichuan University, Chengdu, China.
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
| | - Hengyi Cao
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
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Van Dyken PC, MacKinley M, Khan AR, Palaniyappan L. Cortical Network Disruption Is Minimal in Early Stages of Psychosis. SCHIZOPHRENIA BULLETIN OPEN 2024; 5:sgae010. [PMID: 39144115 PMCID: PMC11207789 DOI: 10.1093/schizbullopen/sgae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Background and Hypothesis Schizophrenia is associated with white matter disruption and topological reorganization of cortical connectivity but the trajectory of these changes, from the first psychotic episode to established illness, is poorly understood. Current studies in first-episode psychosis (FEP) patients using diffusion magnetic resonance imaging (dMRI) suggest such disruption may be detectable at the onset of psychosis, but specific results vary widely, and few reports have contextualized their findings with direct comparison to young adults with established illness. Study Design Diffusion and T1-weighted 7T MR scans were obtained from N = 112 individuals (58 with untreated FEP, 17 with established schizophrenia, 37 healthy controls) recruited from London, Ontario. Voxel- and network-based analyses were used to detect changes in diffusion microstructural parameters. Graph theory metrics were used to probe changes in the cortical network hierarchy and to assess the vulnerability of hub regions to disruption. The analysis was replicated with N = 111 (57 patients, 54 controls) from the Human Connectome Project-Early Psychosis (HCP-EP) dataset. Study Results Widespread microstructural changes were found in people with established illness, but changes in FEP patients were minimal. Unlike the established illness group, no appreciable topological changes in the cortical network were observed in FEP patients. These results were replicated in the early psychosis patients of the HCP-EP datasets, which were indistinguishable from controls in most metrics. Conclusions The white matter structural changes observed in established schizophrenia are not a prominent feature in the early stages of this illness.
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Affiliation(s)
- Peter C Van Dyken
- Neuroscience Graduate Program, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Michael MacKinley
- Lawson Health Research Institute, London Health Sciences Centre, London, ON, Canada
| | - Ali R Khan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Lena Palaniyappan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, London, ON, Canada
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
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Nerland S, Slapø NB, Barth C, Mørch-Johnsen L, Jørgensen KN, Beck D, Wortinger LA, Westlye LT, Jönsson EG, Andreassen OA, Maximov II, Geier OM, Agartz I. Current Auditory Hallucinations Are Not Associated With Specific White Matter Diffusion Alterations in Schizophrenia. SCHIZOPHRENIA BULLETIN OPEN 2024; 5:sgae008. [PMID: 39144116 PMCID: PMC11207682 DOI: 10.1093/schizbullopen/sgae008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Background and Hypothesis Studies have linked auditory hallucinations (AH) in schizophrenia spectrum disorders (SCZ) to altered cerebral white matter microstructure within the language and auditory processing circuitry (LAPC). However, the specificity to the LAPC remains unclear. Here, we investigated the relationship between AH and DTI among patients with SCZ using diffusion tensor imaging (DTI). Study Design We included patients with SCZ with (AH+; n = 59) and without (AH-; n = 81) current AH, and 140 age- and sex-matched controls. Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were extracted from 39 fiber tracts. We used principal component analysis (PCA) to identify general factors of variation across fiber tracts and DTI metrics. Regression models adjusted for sex, age, and age2 were used to compare tract-wise DTI metrics and PCA factors between AH+, AH-, and healthy controls and to assess associations with clinical characteristics. Study Results Widespread differences relative to controls were observed for MD and RD in patients without current AH. Only limited differences in 2 fiber tracts were observed between AH+ and controls. Unimodal PCA factors based on MD, RD, and AD, as well as multimodal PCA factors, differed significantly relative to controls for AH-, but not AH+. We did not find any significant associations between PCA factors and clinical characteristics. Conclusions Contrary to previous studies, DTI metrics differed mainly in patients without current AH compared to controls, indicating a widespread neuroanatomical distribution. This challenges the notion that altered DTI metrics within the LAPC is a specific feature underlying AH.
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Affiliation(s)
- Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nora Berz Slapø
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lynn Mørch-Johnsen
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry, Østfold Hospital, Grålum, Norway
- Department of Clinical Research, Østfold Hospital, Grålum, Norway
| | - Kjetil Nordbø Jørgensen
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dani Beck
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Laura A Wortinger
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Erik G Jönsson
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Ole A Andreassen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ivan I Maximov
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
| | - Oliver M Geier
- Department of Computational Radiology and Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
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12
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Seitz-Holland J, Nägele FL, Kubicki M, Pasternak O, Cho KIK, Hough M, Mulert C, Shenton ME, Crow TJ, James ACD, Lyall AE. Shared and distinct white matter abnormalities in adolescent-onset schizophrenia and adolescent-onset psychotic bipolar disorder. Psychol Med 2023; 53:4707-4719. [PMID: 35796024 PMCID: PMC11119277 DOI: 10.1017/s003329172200160x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND While adolescent-onset schizophrenia (ADO-SCZ) and adolescent-onset bipolar disorder with psychosis (psychotic ADO-BPD) present a more severe clinical course than their adult forms, their pathophysiology is poorly understood. Here, we study potentially state- and trait-related white matter diffusion-weighted magnetic resonance imaging (dMRI) abnormalities along the adolescent-onset psychosis continuum to address this need. METHODS Forty-eight individuals with ADO-SCZ (20 female/28 male), 15 individuals with psychotic ADO-BPD (7 female/8 male), and 35 healthy controls (HCs, 18 female/17 male) underwent dMRI and clinical assessments. Maps of extracellular free-water (FW) and fractional anisotropy of cellular tissue (FAT) were compared between individuals with psychosis and HCs using tract-based spatial statistics and FSL's Randomise. FAT and FW values were extracted, averaged across all voxels that demonstrated group differences, and then utilized to test for the influence of age, medication, age of onset, duration of illness, symptom severity, and intelligence. RESULTS Individuals with adolescent-onset psychosis exhibited pronounced FW and FAT abnormalities compared to HCs. FAT reductions were spatially more widespread in ADO-SCZ. FW increases, however, were only present in psychotic ADO-BPD. In HCs, but not in individuals with adolescent-onset psychosis, FAT was positively related to age. CONCLUSIONS We observe evidence for cellular (FAT) and extracellular (FW) white matter abnormalities in adolescent-onset psychosis. Although cellular white matter abnormalities were more prominent in ADO-SCZ, such alterations may reflect a shared trait, i.e. neurodevelopmental pathology, present across the psychosis spectrum. Extracellular abnormalities were evident in psychotic ADO-BPD, potentially indicating a more dynamic, state-dependent brain reaction to psychosis.
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Affiliation(s)
- Johanna Seitz-Holland
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Felix L. Nägele
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Kang Ik K. Cho
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Morgan Hough
- SANE POWIC, University Department of Psychiatry, Warneford Hospital, Oxford, UK
- Highfield Unit, University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - Christoph Mulert
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
- Centre for Psychiatry and Psychotherapy, Justus-Liebig-University, Giessen, Germany
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Timothy J. Crow
- SANE POWIC, University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - Anthony C. D. James
- SANE POWIC, University Department of Psychiatry, Warneford Hospital, Oxford, UK
- Highfield Unit, University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - Amanda E. Lyall
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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13
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Serpa M, Doshi J, Joaquim HPG, Vieira ELM, Erus G, Chaim-Avancini TM, Cavallet M, Guglielmi LG, Sallet PC, Talib L, Teixeira AL, van de Bilt MT, McGuire P, Gattaz WF, Davatzikos C, Busatto GF, Zanetti MV. Inflammatory cytokines and white matter microstructure in the acute phase of first-episode psychosis: A longitudinal study. Schizophr Res 2023; 257:5-18. [PMID: 37230043 DOI: 10.1016/j.schres.2023.05.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/14/2023] [Accepted: 05/06/2023] [Indexed: 05/27/2023]
Abstract
OBJECTIVES Schizophrenia-related psychosis is associated with abnormalities in white matter (WM) microstructure and structural brain dysconnectivity. However, the pathological process underlying such changes is unknown. We sought to investigate the potential association between peripheral cytokine levels and WM microstructure during the acute phase of first-episode psychosis (FEP) in a cohort of drug-naïve patients. METHODS Twenty-five non-affective FEP patients and 69 healthy controls underwent MRI scanning and blood collection at study entry. After achieving clinical remission, 21 FEP were reassessed; 38 age and biological sex-matched controls also had a second assessment. We measured fractional anisotropy (FA) of selected WM regions-of-interest (ROIs) and plasma levels of four cytokines (IL-6, IL-10, IFN-γ, and TNF-α). RESULTS At baseline (acute psychosis), the FEP group showed reduced FA relative to controls in half the examined ROIs. Within the FEP group, IL-6 levels were negatively correlated with FA values. Longitudinally, patients showed increments of FA in several ROIs affected at baseline, and such changes were associated with reductions in IL-6 levels. CONCLUSIONS A state-dependent process involving an interplay between a pro-inflammatory cytokine and brain WM might be associated with the clinical manifestation of FEP. This association suggests a deleterious effect of IL-6 on WM tracts during the acute phase of psychosis.
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Affiliation(s)
- Mauricio Serpa
- Laboratory of Psychiatric Neuroimaging (LIM21), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil; Laboratory of Neuroscience (LIM27), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
| | - Jimit Doshi
- Section of Biomedical Image Analysis (SBIA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Helena P G Joaquim
- Laboratory of Neuroscience (LIM27), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Erica L M Vieira
- Universidade Federal de Minas Gerais, Faculdade de Medicina, Belo Horizonte, MG, Brazil
| | - Guray Erus
- Section of Biomedical Image Analysis (SBIA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Tiffany M Chaim-Avancini
- Laboratory of Psychiatric Neuroimaging (LIM21), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Mikael Cavallet
- Laboratory of Psychiatric Neuroimaging (LIM21), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Luiza Guilherme Guglielmi
- Laboratory of Immunology, Instituto do Coracao (INCOR), Hospital das Clinicas FMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Paulo C Sallet
- Laboratory of Neuroscience (LIM27), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Leda Talib
- Laboratory of Neuroscience (LIM27), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Antonio L Teixeira
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston (UTHealth), Houston, TX, USA
| | - Martinus T van de Bilt
- Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil; Laboratory of Neuroscience (LIM27), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; NIHR Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Wagner F Gattaz
- Laboratory of Neuroscience (LIM27), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Christos Davatzikos
- Section of Biomedical Image Analysis (SBIA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Geraldo F Busatto
- Laboratory of Psychiatric Neuroimaging (LIM21), Department and Institute of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil
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14
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León-Ortiz P, Reyes-Madrigal F, Kochunov P, Gómez-Cruz G, Moncada-Habib T, Malacara M, Mora-Durán R, Rowland LM, de la Fuente-Sandoval C. White matter alterations and the conversion to psychosis: A combined diffusion tensor imaging and glutamate 1H MRS study. Schizophr Res 2022; 249:85-92. [PMID: 32595100 PMCID: PMC10025976 DOI: 10.1016/j.schres.2020.06.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 06/08/2020] [Accepted: 06/10/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Widespread white matter abnormalities and alterations in glutamate levels have been reported in patients with schizophrenia. We hypothesized that alterations in white matter integrity and glutamate levels in individuals at clinical high risk (CHR) for psychosis are associated with the subsequent development of psychosis. METHODS Participants included 33 antipsychotic naïve CHR (Female 7/Male 26, Age 19.55 (4.14) years) and 38 healthy controls (Female 10/Male 28, Age 20.92 (3.37) years). Whole brain diffusion tensor imaging for fractional anisotropy (FA) and right frontal white matter proton magnetic resonance spectroscopy for glutamate levels were acquired. CHR participants were clinically followed for 2 years to determine conversion to psychosis. RESULTS CHR participants that transitioned to psychosis (N = 7, 21%) were characterized by significantly lower FA values in the posterior thalamic radiation compared to those who did not transition and healthy controls. In the CHR group that transitioned to psychosis only, positive exploratory correlations between glutamate levels and FA values of the posterior thalamic radiation and the retrolenticular part of the internal capsule and a negative correlation between glutamate levels and the cingulum FA values were found. CONCLUSION The results of the present study highlight that alterations in white matter structure and glutamate are related with the conversion to psychosis.
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Affiliation(s)
- Pablo León-Ortiz
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico; Department of Education, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Francisco Reyes-Madrigal
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, United States of America
| | - Gladys Gómez-Cruz
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Tomás Moncada-Habib
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Melanie Malacara
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Ricardo Mora-Durán
- Emergency Department, Hospital Fray Bernardino Álvarez, Mexico City, Mexico
| | - Laura M Rowland
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, United States of America
| | - Camilo de la Fuente-Sandoval
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico; Neuropsychiatry Department, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico.
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Diamond A, Silverstein SM, Keane BP. Visual system assessment for predicting a transition to psychosis. Transl Psychiatry 2022; 12:351. [PMID: 36038544 PMCID: PMC9424317 DOI: 10.1038/s41398-022-02111-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 08/08/2022] [Accepted: 08/11/2022] [Indexed: 01/19/2023] Open
Abstract
The field of psychiatry is far from perfect in predicting which individuals will transition to a psychotic disorder. Here, we argue that visual system assessment can help in this regard. Such assessments have generated medium-to-large group differences with individuals prior to or near the first psychotic episode or have shown little influence of illness duration in larger samples of more chronic patients. For example, self-reported visual perceptual distortions-so-called visual basic symptoms-occur in up to 2/3rds of those with non-affective psychosis and have already longitudinally predicted an impending onset of schizophrenia. Possibly predictive psychophysical markers include enhanced contrast sensitivity, prolonged backward masking, muted collinear facilitation, reduced stereoscopic depth perception, impaired contour and shape integration, and spatially restricted exploratory eye movements. Promising brain-based markers include visual thalamo-cortical hyperconnectivity, decreased occipital gamma band power during visual detection (MEG), and reduced visually evoked occipital P1 amplitudes (EEG). Potentially predictive retinal markers include diminished cone a- and b-wave amplitudes and an attenuated photopic flicker response during electroretinography. The foregoing assessments are often well-described mechanistically, implying that their findings could readily shed light on the underlying pathophysiological changes that precede or accompany a transition to psychosis. The retinal and psychophysical assessments in particular are inexpensive, well-tolerated, easy to administer, and brief, with few inclusion/exclusion criteria. Therefore, across all major levels of analysis-from phenomenology to behavior to brain and retinal functioning-visual system assessment could complement and improve upon existing methods for predicting which individuals go on to develop a psychotic disorder.
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Affiliation(s)
- Alexander Diamond
- Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY, USA
| | - Steven M Silverstein
- Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY, USA
- Department of Neuroscience, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY, USA
- Center for Visual Science, University of Rochester, 601 Elmwood Ave, Rochester, NY, USA
- Department of Ophthalmology, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY, USA
| | - Brian P Keane
- Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY, USA.
- Department of Neuroscience, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY, USA.
- Center for Visual Science, University of Rochester, 601 Elmwood Ave, Rochester, NY, USA.
- Department of Brain & Cognitive Sciences, University of Rochester, 358 Meliora Hall, NY, Rochester, USA.
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16
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Cortical surface abnormalities are different depending on the stage of schizophrenia: A cross-sectional vertexwise mega-analysis of thickness, area and gyrification. Schizophr Res 2021; 236:104-114. [PMID: 34481405 DOI: 10.1016/j.schres.2021.08.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 05/28/2021] [Accepted: 08/09/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND Brain magnetic resonance imaging studies have not investigated the cortical surface comprehensively in schizophrenia subjects by assessing thickness, surface area and gyrification separately during the first-episode of psychosis (FEP) or chronic schizophrenia (ChSch). METHODS We investigated cortical surface abnormalities in 137 FEP patients and 240 ChSch subjects compared to 297 Healthy Controls (HC) contributed by five cohorts. Maps showing results of vertexwise between-group comparisons of cortical thickness, area, and gyrification were produced using T1-weighted datasets processed using FreeSurfer 5.3, followed by validated quality control protocols. RESULTS FEP subjects showed large clusters of increased area and gyrification relative to HC in prefrontal and insuli cortices (Cohen's d: 0.049 to 0.28). These between-group differences occurred partially beyond the effect of sample. ChSch subjects displayed reduced cortical thickness relative to HC in smaller fronto-temporal foci (d: -0.73 to -0.35), but not beyond the effect of sample. Differences between FEP and HC subjects were associated with male gender, younger age, and earlier illness onset, while differences between ChSch and HC were associated with treatment-resistance and first-generation antipsychotic (FGA) intake independently of sample effect. CONCLUSIONS Separate assessments of FEP and ChSch revealed abnormalities that differed in regional distribution, phenotypes affected and effect size. In FEP, associations of greater cortical area and gyrification abnormalities with earlier age of onset suggest an origin on anomalous neurodevelopment, while thickness reductions in ChSch are at least partially explained by treatment-resistance and FGA intake. Associations of between-group differences with clinical variables retained statistical significance beyond the effect of sample.
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17
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Seitz-Holland J, Cetin-Karayumak S, Wojcik JD, Lyall A, Levitt J, Shenton ME, Pasternak O, Westin CF, Baxi M, Kelly S, Mesholam-Gately R, Vangel M, Pearlson G, Tamminga CA, Sweeney JA, Clementz BA, Schretlen D, Viher PV, Stegmayer K, Walther S, Lee J, Crow T, James A, Voineskos A, Buchanan RW, Szeszko PR, Malhotra AK, Rathi Y, Keshavan M, Kubicki M. Elucidating the relationship between white matter structure, demographic, and clinical variables in schizophrenia-a multicenter harmonized diffusion tensor imaging study. Mol Psychiatry 2021; 26:5357-5370. [PMID: 33483689 PMCID: PMC8329919 DOI: 10.1038/s41380-021-01018-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 11/24/2020] [Accepted: 01/05/2021] [Indexed: 01/30/2023]
Abstract
White matter (WM) abnormalities are repeatedly demonstrated across the schizophrenia time-course. However, our understanding of how demographic and clinical variables interact, influence, or are dependent on WM pathologies is limited. The most well-known barriers to progress are heterogeneous findings due to small sample sizes and the confounding influence of age on WM. The present study leverages access to the harmonized diffusion magnetic-resonance-imaging data and standardized clinical data from 13 international sites (597 schizophrenia patients (SCZ)). Fractional anisotropy (FA) values for all major WM structures in patients were predicted based on FA models estimated from a healthy population (n = 492). We utilized the deviations between predicted and real FA values to answer three essential questions. (1) "Which clinical variables explain WM abnormalities?". (2) "Does the degree of WM abnormalities predict symptom severity?". (3) "Does sex influence any of those relationships?". Regression and mediator analyses revealed that a longer duration-of-illness is associated with more severe WM abnormalities in several tracts. In addition, they demonstrated that a higher antipsychotic medication dose is related to more severe corpus callosum abnormalities. A structural equation model revealed that patients with more WM abnormalities display higher symptom severity. Last, the results exhibited sex-specificity. Males showed a stronger association between duration-of-illness and WM abnormalities. Females presented a stronger association between WM abnormalities and symptom severity, with IQ impacting this relationship. Our findings provide clear evidence for the interaction of demographic, clinical, and behavioral variables with WM pathology in SCZ. Our results also point to the need for longitudinal studies, directly investigating the casualty and sex-specificity of these relationships, as well as the impact of cognitive resiliency on structure-function relationships.
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Affiliation(s)
- Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joanne D Wojcik
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Amanda Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - James Levitt
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Brockton, MA, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Brockton, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Carl-Fredrik Westin
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Madhura Baxi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Graduate Program of Neuroscience, Boston University, Boston, MA, USA
| | - Sinead Kelly
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Raquelle Mesholam-Gately
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Mark Vangel
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Brett A Clementz
- Department of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - David Schretlen
- Department of Psychiatry and Behavioral Sciences, Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Petra Verena Viher
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Katharina Stegmayer
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Sebastian Walther
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Jungsun Lee
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Tim Crow
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Anthony James
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Aristotle Voineskos
- Center for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Philip R Szeszko
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center, Bronx, New York, NY, USA
| | - Anil K Malhotra
- The Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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The effect of antipsychotic medications on white matter integrity in first-episode drug-naïve patients with psychosis: A review of DTI studies. Asian J Psychiatr 2021; 61:102688. [PMID: 34000500 DOI: 10.1016/j.ajp.2021.102688] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 04/29/2021] [Accepted: 05/06/2021] [Indexed: 01/10/2023]
Abstract
BACKGROUND Psychotic episodes have been associated with damage to both grey matter (GM) and white matter (WM). Although a recent meta-analysis suggest that in long term treatment, first generation antipsychotics (FGA) are associated with progressive reduction in GM, second generation antipsychotics (SGA) seem to have benefits to WM microstructure. METHODS A search was conducted to identify controlled trials published from January 2000 to January 2021, which assessed WM integrity as measured by DTI in drug-naïve patients with FEP before and after antipsychotic administration. RESULTS 3 studies met the criteria for inclusion. All studies demonstrated lower FA in psychotic patients vs HC. A 6-week study reported that antipsychotic medication results in a further decrease in FA within the bilateral ACG and right ACR, regions important in emotional processing. An 8-week study found that antipsychotic treatment increase FA in the SLF, resulting in improved symptoms and increased processing speed. A 3rd study found an increase in FA in several regions along with a negative correlation between FA and PANSS at remission. CONCLUSIONS Drug-naïve FEP patients have WM dysfunction at baseline and antipsychotic medications appear to alter or improve WM especially at remission. More controlled trials are warranted to validate these conclusions.
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19
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Dynamic functional connectivity and its anatomical substrate reveal treatment outcome in first-episode drug-naïve schizophrenia. Transl Psychiatry 2021; 11:282. [PMID: 33980821 PMCID: PMC8115129 DOI: 10.1038/s41398-021-01398-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 04/09/2021] [Accepted: 04/20/2021] [Indexed: 02/06/2023] Open
Abstract
Convergent evidence has suggested a significant effect of antipsychotic exposure on brain structure and function in patients with schizophrenia, yet the characteristics of favorable treatment outcome remains largely unknown. In this work, we aimed to examine how large-scale brain networks are modulated by antipsychotic treatment, and whether the longitudinal changes could track the improvements of psychopathologic scores. Thirty-four patients with first-episode drug-naïve schizophrenia and 28 matched healthy controls were recruited at baseline from Shanghai Mental Health Center. After 8 weeks of antipsychotic treatment, 24 patients were re-scanned. Through a systematical dynamic functional connectivity (dFC) analysis, we investigated the schizophrenia-related intrinsic alterations of dFC at baseline, followed by a longitudinal study to examine the influence of antipsychotic treatment on these abnormalities by comparing patients at baseline and follow-up. A structural connectivity (SC) association analysis was further carried out to investigate longitudinal anatomical changes that underpin the alterations of dFC. We found a significant symptomatic improvement-related increase in the occurrence of a dFC state characterized by stronger inter-network integration. Furthermore, symptom reduction was correlated with increased FC variability in a unique connectomic signature, particularly in the connections within the default mode network and between the auditory, cognitive control, and cerebellar network to other networks. Additionally, we observed that the SC between the superior frontal gyrus and medial prefrontal cortex was decreased after treatment, suggesting a relaxation of normal constraints on dFC. Taken together, these findings provide new evidence to extend the dysconnectivity hypothesis in schizophrenia from static to dynamic brain network. Moreover, our identified neuroimaging markers tied to the neurobiology of schizophrenia could be used as potential indicators in predicting the treatment outcome of antipsychotics.
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20
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Pawełczyk A, Łojek E, Żurner N, Gawłowska-Sawosz M, Gębski P, Pawełczyk T. The correlation between white matter integrity and pragmatic language processing in first episode schizophrenia. Brain Imaging Behav 2021; 15:1068-1084. [PMID: 32710335 PMCID: PMC8032571 DOI: 10.1007/s11682-020-00314-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Objective: Higher-order language disturbances could be the result of white matter tract abnormalities. The study explores the relationship between white matter and pragmatic skills in first-episode schizophrenia. Methods: Thirty-four first-episode patients with schizophrenia and 32 healthy subjects participated in a pragmatic language and Diffusion Tensor Imaging study, where fractional anisotropy of the arcuate fasciculus, corpus callosum and cingulum was correlated with the Polish version of the Right Hemisphere Language Battery. Results: The patients showed reduced fractional anisotropy in the right arcuate fasciculus, left anterior cingulum bundle and left forceps minor. Among the first episode patients, reduced understanding of written metaphors correlated with reduced fractional anisotropy of left forceps minor, and greater explanation of written and picture metaphors correlated with reduced fractional anisotropy of the left anterior cingulum. Conclusions: The white matter dysfunctions may underlie the pragmatic language impairment in schizophrenia. Our results shed further light on the functional neuroanatomical basis of pragmatic language use by patients with schizophrenia.
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Affiliation(s)
- Agnieszka Pawełczyk
- Department of Affective and Psychotic Disorders, Medical University of Łódź, Łódź, Poland.
| | | | - Natalia Żurner
- Adolescent Ward, Central Clinical Hospital of Medical University of Łódź, Łódź, Poland
| | | | - Piotr Gębski
- Scanlab Diagnostyka Medyczna Księży Młyn, Medical Examination Centre, Medical University of Łódź, Łódź, Poland
| | - Tomasz Pawełczyk
- Department of Affective and Psychotic Disorders, Medical University of Łódź, Łódź, Poland
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21
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Thomas MB, Raghava JM, Pantelis C, Rostrup E, Nielsen MØ, Jensen MH, Glenthøj BY, Mandl RCW, Ebdrup BH, Fagerlund B. Associations between cognition and white matter microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls: A multivariate pattern analysis. Cortex 2021; 139:282-297. [PMID: 33933719 DOI: 10.1016/j.cortex.2021.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 01/19/2021] [Accepted: 03/01/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Cognitive functions have been associated with white matter (WM) microstructure in schizophrenia, but most studies are limited by examining only select cognitive measures and single WM tracts in chronic, medicated patients. It is unclear if the cognition-WM relationship differs between antipsychotic-naïve patients with schizophrenia and healthy controls, as differential associations have not been directly examined. Here we examine if there are differential patterns of associations between cognition and WM microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls, and we characterize reliable contributors to the pattern of associations across multiple cognitive domains and WM regions, in order to elucidate white matter contribution to the neural underpinnings of cognitive deficits. METHODS Thirty-six first-episode antipsychotic-naïve patients with schizophrenia and 52 matched healthy controls underwent cognitive tests and diffusion-weighted imaging on a 3T Magnetic Resonance Imaging scanner. Using a multivariate partial least squares correlation analysis, we included 14 cognitive variables and mean fractional anisotropy values of 48 WM regions. RESULTS Initial analyses showed significant group differences in both measures of WM and cognition. There was no group interaction effect in the pattern of associations between cognition and WM microstructure. The combined analysis of patients and controls lead to a significant pattern of associations (omnibus test p = .015). Thirty-four regions and seven cognitive functions contributed reliably to the associations. CONCLUSIONS The lack of an interaction effect suggests similar associations in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls. This, together with the differences in both WM and cognitive measurements, supports the involvement of WM in cognitive deficits in schizophrenia. Our findings add to the field by showing a coherent picture of the overall pattern of association between cognition and WM. These findings increase our understanding of the impact of WM on cognition, contributing to the search for neuromarkers of cognitive deficits in schizophrenia.
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Affiliation(s)
- Marie B Thomas
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark.
| | - Jayachandra M Raghava
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Christos Pantelis
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, Victoria, Australia.
| | - Egill Rostrup
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Mette Ø Nielsen
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Maria H Jensen
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Birte Y Glenthøj
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - René C W Mandl
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; UMC Brain Center, University Medical Center Utrecht, Utrecht, Netherlands.
| | - Bjørn H Ebdrup
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Birgitte Fagerlund
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark.
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22
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Faria AV, Zhao Y, Ye C, Hsu J, Yang K, Cifuentes E, Wang L, Mori S, Miller M, Caffo B, Sawa A. Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup. Hum Brain Mapp 2020; 42:1034-1053. [PMID: 33377594 PMCID: PMC7856640 DOI: 10.1002/hbm.25276] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 09/29/2020] [Accepted: 10/18/2020] [Indexed: 02/06/2023] Open
Abstract
Multi‐institutional brain imaging studies have emerged to resolve conflicting results among individual studies. However, adjusting multiple variables at the technical and cohort levels is challenging. Therefore, it is important to explore approaches that provide meaningful results from relatively small samples at institutional levels. We studied 87 first episode psychosis (FEP) patients and 62 healthy subjects by combining supervised integrated factor analysis (SIFA) with a novel pipeline for automated structure‐based analysis, an efficient and comprehensive method for dimensional data reduction that our group recently established. We integrated multiple MRI features (volume, DTI indices, resting state fMRI—rsfMRI) in the whole brain of each participant in an unbiased manner. The automated structure‐based analysis showed widespread DTI abnormalities in FEP and rs‐fMRI differences between FEP and healthy subjects mostly centered in thalamus. The combination of multiple modalities with SIFA was more efficient than the use of single modalities to stratify a subgroup of FEP (individuals with schizophrenia or schizoaffective disorder) that had more robust deficits from the overall FEP group. The information from multiple MRI modalities and analytical methods highlighted the thalamus as significantly abnormal in FEP. This study serves as a proof‐of‐concept for the potential of this methodology to reveal disease underpins and to stratify populations into more homogeneous sub‐groups.
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Affiliation(s)
- Andreia V Faria
- Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Yi Zhao
- Department of Biostatistics, Indiana University, School of Medicine, Indianapolis, Indiana, USA
| | - Chenfei Ye
- Department of Electronics and Information, Harbin Institute of Technology Shenzhen Graduate School, Guangdong, China
| | - Johnny Hsu
- Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kun Yang
- Department Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Elizabeth Cifuentes
- Department Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences and Radiology, Northwestern University, Evanston, Illinois, USA
| | - Susumu Mori
- Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Michael Miller
- Department of Biomedical Engineering, The Whiting School of Engineering, Baltimore, Maryland, USA
| | - Brian Caffo
- Department of Biostatistics, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Akira Sawa
- Department Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, The Whiting School of Engineering, Baltimore, Maryland, USA.,Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Mental Health, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
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23
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Germann J, Gouveia FV, Martinez RCR, Zanetti MV, de Souza Duran FL, Chaim-Avancini TM, Serpa MH, Chakravarty MM, Devenyi GA. Fully Automated Habenula Segmentation Provides Robust and Reliable Volume Estimation Across Large Magnetic Resonance Imaging Datasets, Suggesting Intriguing Developmental Trajectories in Psychiatric Disease. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 5:923-929. [PMID: 32222276 DOI: 10.1016/j.bpsc.2020.01.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 01/21/2020] [Accepted: 01/22/2020] [Indexed: 01/29/2023]
Abstract
Studies of habenula (Hb) function and structure provided evidence of its involvement in psychiatric disorders, including schizophrenia and bipolar disorder. Previous studies using magnetic resonance imaging (manual/semiautomated segmentation) have reported conflicting results. Aiming to improve Hb segmentation reliability and the study of large datasets, we describe a fully automated protocol that was validated against manual segmentations and applied to 3 datasets (childhood/adolescence and adult bipolar disorder and schizophrenia). It achieved reliable Hb segmentation, providing robust volume estimations across a large age range and varying image acquisition parameters. Applying it to clinically relevant datasets, we found smaller Hb volumes in the adult bipolar disorder dataset and larger volumes in the adult schizophrenia dataset compared with healthy control subjects. There are indications that Hb volume in both groups shows deviating developmental trajectories early in life. This technique sets a precedent for future studies, as it allows for fast and reliable Hb segmentation and will be publicly available.
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Affiliation(s)
- Jürgen Germann
- University Health Network, Toronto, Ontario, Canada; Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada.
| | | | - Raquel C R Martinez
- Division of Neuroscience, Hospital Sírio-Libanês, São Paulo, Brazil; Laboratory of Psychopathology and Psychiaric Therapeutics (LIM-23), Institute of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil
| | - Marcus Vinicius Zanetti
- Division of Neuroscience, Hospital Sírio-Libanês, São Paulo, Brazil; Laboratory of Psychiatric Neuroimaging (LIM-21), Institute of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil
| | - Fábio Luís de Souza Duran
- Laboratory of Psychiatric Neuroimaging (LIM-21), Institute of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil
| | - Tiffany M Chaim-Avancini
- Laboratory of Psychiatric Neuroimaging (LIM-21), Institute of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil
| | - Mauricio H Serpa
- Laboratory of Psychiatric Neuroimaging (LIM-21), Institute of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
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Fan Y, Liu J, Zeng LL, Dong Q, Su J, Peng L, Shen H, Lu X, Sun J, Zhang L, Wang M, Raj J, Liu B, Hu D, Li L. State-Independent and -Dependent Structural Connectivity Alterations in Depression. Front Psychiatry 2020; 11:568717. [PMID: 33329107 PMCID: PMC7733996 DOI: 10.3389/fpsyt.2020.568717] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 11/09/2020] [Indexed: 12/31/2022] Open
Abstract
Some brain abnormalities persist at the remission phase, that is, the state-independent abnormalities, which may be one of the reasons for the high recurrence of major depressive disorder (MDD). Hence, it is of great significance to identify state-independent abnormalities of MDD through longitudinal investigation. Ninety-nine MDD patients and 118 healthy controls (HCs) received diffusion tensor imaging scanning at baseline. After 6-month antidepressant treatment, 68 patients received a second scan, among which 59 patients achieved full clinical remission. Differences in whole-brain structural connectivity (SC) between patients with MDD at baseline and HCs were estimated by two-sample t-tests. Masked with significantly changed SCs in MDD, two-sample t-tests were conducted between the remitted MDD subgroup at follow-up and HCs, and paired t-tests were implemented to compare the differences of SC in the remitted MDD subgroup before and after treatment. Significantly decreased SC between the right insula and the anterior temporal cortex (ATC), between the right ATC and the posterior temporal cortex (PTC), between the left ATC and the auditory cortex as well as increased connectivity between the right posterior cingulate cortex (PCC) and the left medial parietal cortex (MPC) were observed in the MDD group compared with the HC group at baseline (p < 0.05, FDR corrected). The decreased connectivity between the right insula and the ATC and increased connectivity between the right PCC and the left MPC persisted in the remitted MDD subgroup at follow-up (p < 0.05, FDR corrected). The decreased SC between the right insula and the ATC and increased SC between the right PCC and left MPC showed state-independent characters, which may be implicated in the sustained negative attention bias and motor retardation in MDD. In contrast, the decreased SC between the right ATC and the PTC and between the left ATC and the auditory cortex seemed to be state-dependent.
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Affiliation(s)
- Yiming Fan
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
| | - Jin Liu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Mental Health Institute of Central South University, Changsha, China
| | - Ling-Li Zeng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
| | - Qiangli Dong
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Mental Health Institute of Central South University, Changsha, China
| | - Jianpo Su
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
| | - Limin Peng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
| | - Hui Shen
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
| | - Xiaowen Lu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Mental Health Institute of Central South University, Changsha, China
| | - Jinrong Sun
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Mental Health Institute of Central South University, Changsha, China
| | - Liang Zhang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Mental Health Institute of Central South University, Changsha, China
| | - Mi Wang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Mental Health Institute of Central South University, Changsha, China
| | - Jugessur Raj
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Mental Health Institute of Central South University, Changsha, China
| | - Bangshan Liu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Mental Health Institute of Central South University, Changsha, China
| | - Dewen Hu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
| | - Lingjiang Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Mental Health Institute of Central South University, Changsha, China
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A comparison of regional brain volumes and white matter connectivity in subjects with stimulant induced psychosis versus schizophrenia. Psychopharmacology (Berl) 2019; 236:3385-3399. [PMID: 31230145 DOI: 10.1007/s00213-019-05298-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 06/05/2019] [Indexed: 12/31/2022]
Abstract
RATIONALE Schizophrenia and stimulant-induced psychosis (SIP) represent two different forms of psychotic disorder, with different etiologies. While many of the symptoms of psychosis are common to both disorders, there have been few direct comparisons between these conditions, especially when controlling for stimulant use in individuals with schizophrenia. OBJECTIVES We directly compared both psychotic disorders with a comprehensive battery of clinical, neurocognitive and neuroanatomical measures. This included one group with SIP (and concurrent stimulant dependence) and two groups with schizophrenia (either with or without concurrent stimulant dependence). METHODS Ninety-six participants were recruited from a marginalized urban population, which included 39 with SIP (and concurrent stimulant dependence), 18 with schizophrenia (without stimulant dependence), and 39 with schizophrenia (with concurrent stimulant dependence). All subjects had extensive clinical and neurocognitive evaluations, complemented with structural MRI including diffusion tensor imaging (DTI) sequences to determine regional brain volumes and white matter connectivity. RESULTS Both positive and negative symptoms were greater in the SZ-dependent group than the other two. Neurocognitive function was broadly similar. The structural brain imaging revealed lateralized changes to the left parietal/temporal lobe, in which regional volumes were smaller in the SZ-dependent than the SZ-non-dependent group. DTI analysis indicated extensive decreases in fractional anisotropy, with parallel increases in radial diffusivity, in the SIP group compared to the SZ-dependent group. CONCLUSIONS These findings reveal both similarities and differences between SIP and schizophrenia. Furthermore, schizophrenia with concurrent stimulant dependence may be associated with a different clinical and neuroanatomical profile as compared to schizophrenia alone.
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Tomyshev AS, Lebedeva IS, Akhadov TA, Omelchenko MA, Rumyantsev AO, Kaleda VG. Alterations in white matter microstructure and cortical thickness in individuals at ultra-high risk of psychosis: A multimodal tractography and surface-based morphometry study. Psychiatry Res Neuroimaging 2019; 289:26-36. [PMID: 31132567 DOI: 10.1016/j.pscychresns.2019.05.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 02/24/2019] [Accepted: 05/08/2019] [Indexed: 12/11/2022]
Abstract
There is increasing evidence of white matter (WM) and grey matter pathology in subjects at ultra-high risk of psychosis (UHR), although a limited number of diffusion-weighted magnetic resonance imaging (DW-MRI) and surface-based morphometry (SBM) studies have revealed anatomically inconsistent results. The present multimodal study applies tractography and SBM to analyze WM microstructure, whole-brain cortical anatomy, and potential interconnections between WM and grey matter abnormalities in UHR subjects. Thirty young male UHR patients and 30 healthy controls underwent DW-MRI and T1-weighted MRI. Fractional anisotropy; mean, radial, and axial diffusivity in 18 WM tracts; and vertex-based cortical thickness, area, and volume were analyzed. We found increased radial diffusivity in the left anterior thalamic radiation and reduced bilateral thickness across the frontal, temporal, and parietal cortices. No correlations between WM and grey matter abnormalities were identified. These results provide further evidence that WM microstructure abnormalities and cortical anatomical changes occur in the UHR state. Disruption of structural connectivity in the prefrontal-subcortical circuitry, likely caused by myelin pathology, and cortical thickness reduction affecting the networks presumably involved in processing and coordination of external and internal information streams may underlie the widespread deficits in neurocognitive and social functioning that are consistently reported in UHR subjects.
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Affiliation(s)
- Alexander S Tomyshev
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, 34 Kashirskoe shosse, 115522 Moscow, Russia.
| | - Irina S Lebedeva
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, 34 Kashirskoe shosse, 115522 Moscow, Russia
| | - Tolibdzhon A Akhadov
- Department of Radiology, Children's Clinical and Research Institute of Emergency Surgery and Trauma, Moscow, Russia
| | - Maria A Omelchenko
- Department of Endogenous Mental Disorders, Mental Health Research Center, Moscow, Russia
| | - Andrey O Rumyantsev
- Department of Endogenous Mental Disorders, Mental Health Research Center, Moscow, Russia
| | - Vasiliy G Kaleda
- Department of Endogenous Mental Disorders, Mental Health Research Center, Moscow, Russia
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Subtle white matter alterations in schizophrenia identified with a new measure of fiber density. Sci Rep 2019; 9:4636. [PMID: 30874571 PMCID: PMC6420505 DOI: 10.1038/s41598-019-40070-2] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 02/07/2019] [Indexed: 12/13/2022] Open
Abstract
Altered cerebral connectivity is one of the core pathophysiological mechanism underlying the development and progression of information-processing deficits in schizophrenia. To date, most diffusion tensor imaging (DTI) studies used fractional anisotropy (FA) to investigate disrupted white matter connections. However, a quantitative interpretation of FA changes is often impeded by the inherent limitations of the underlying tensor model. A more fine-grained measure of white matter alterations could be achieved by measuring fiber density (FD) - a novel non-tensor-derived diffusion marker. This study investigates, for the first time, FD alterations in schizophrenia patients. FD and FA maps were derived from diffusion data of 25 healthy controls (HC) and 21 patients with schizophrenia (SZ). Using tract-based spatial statistics (TBSS), group differences in FD and FA were investigated across the entire white matter. Furthermore, we performed a region of interest (ROI) analysis of frontal fasciculi to detect potential correlations between FD and positive symptoms. As a result, whole brain TBSS analysis revealed reduced FD in SZ patients compared to HC in several white matter tracts including the left and right thalamic radiation (TR), superior longitudinal fasciculus (SLF), corpus callosum (CC), and corticospinal tract (CST). In contrast, there were no significant FA differences between groups. Further, FD values in the TR were negatively correlated with the severity of positive symptoms and medication dose in SZ patients. In summary, a novel diffusion-weighted data analysis approach enabled us to identify widespread FD changes in SZ patients with most prominent white matter alterations in the frontal and subcortical regions. Our findings suggest that the new FD measure may be more sensitive to subtle changes in the white matter microstructure compared to FA, particularly in the given population. Therefore, investigating FD may be a promising approach to detect subtle changes in the white matter microstructure of altered connectivity in schizophrenia.
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Griffa A, Baumann PS, Klauser P, Mullier E, Cleusix M, Jenni R, van den Heuvel MP, Do KQ, Conus P, Hagmann P. Brain connectivity alterations in early psychosis: from clinical to neuroimaging staging. Transl Psychiatry 2019; 9:62. [PMID: 30718455 PMCID: PMC6362225 DOI: 10.1038/s41398-019-0392-y] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 01/10/2019] [Indexed: 12/11/2022] Open
Abstract
Early in the course of psychosis, alterations in brain connectivity accompany the emergence of psychiatric symptoms and cognitive impairments, including processing speed. The clinical-staging model is a refined form of diagnosis that places the patient along a continuum of illness conditions, which allows stage-specific interventions with the potential of improving patient care and outcome. This cross-sectional study investigates brain connectivity features that characterize the clinical stages following a first psychotic episode. Structural brain networks were derived from diffusion-weighted MRI for 71 early-psychosis patients and 76 healthy controls. Patients were classified into stage II (first-episode), IIIa (incomplete remission), IIIb (one relapse), and IIIc (two or more relapses), according to the course of the illness until the time of scanning. Brain connectivity measures and diffusion parameters (fractional anisotropy, apparent diffusion coefficient) were investigated using general linear models and sparse linear discriminant analysis (sLDA), studying distinct subgroups of patients who were at specific stages of early psychosis. We found that brain connectivity impairments were more severe in clinical stages following the first-psychosis episode (stages IIIa, IIIb, IIIc) than in first-episode psychosis (stage II) patients. These alterations were spatially diffuse but converged on a set of vulnerable regions, whose inter-connectivity selectively correlated with processing speed in patients and controls. The sLDA suggested that relapsing-remitting (stages IIIb, IIIc) and non-remitting (stage IIIa) patients are characterized by distinct dysconnectivity profiles. Our results indicate that neuroimaging markers of brain dysconnectivity in early psychosis may reflect the heterogeneity of the illness and provide a connectomics signature of the clinical-staging model.
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Affiliation(s)
- Alessandra Griffa
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland. .,Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands.
| | - Philipp S. Baumann
- 0000 0001 0423 4662grid.8515.9Service of General Psychiatry and Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Paul Klauser
- 0000 0001 0423 4662grid.8515.9Service of General Psychiatry and Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Emeline Mullier
- 0000 0001 0423 4662grid.8515.9Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Martine Cleusix
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Raoul Jenni
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Martijn P. van den Heuvel
- grid.484519.5Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands
| | - Kim Q. Do
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Philippe Conus
- 0000 0001 0423 4662grid.8515.9Service of General Psychiatry and Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Patric Hagmann
- 0000 0001 0423 4662grid.8515.9Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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Wang Y, Deng F, Jia Y, Wang J, Zhong S, Huang H, Chen L, Chen G, Hu H, Huang L, Huang R. Disrupted rich club organization and structural brain connectome in unmedicated bipolar disorder. Psychol Med 2019; 49:510-518. [PMID: 29734951 DOI: 10.1017/s0033291718001150] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Bipolar disorder (BD) has been associated with altered brain structural and functional connectivity. However, little is known regarding alterations of the structural brain connectome in BD. The present study aimed to use diffusion-tensor imaging (DTI) and graph theory approaches to investigate the rich club organization and white matter structural connectome in BD. METHODS Forty-two patients with unmedicated BD depression and 59 age-, sex- and handedness-matched healthy control participants underwent DTI. The whole-brain structural connectome was constructed by a deterministic fiber tracking approach. Graph theory analysis was used to examine the group-specific global and nodal topological properties, and rich club organizations, and then nonparametric permutation tests were used for group comparisons of network parameters. RESULTS Compared with healthy control participants, the patients with BD showed abnormal global properties, including increased characteristic path length, and decreased global efficiency and local efficiency. Locally, the patients with BD showed abnormal nodal parameters (nodal strength, nodal efficiency, and nodal betweenness) predominantly in the parietal, orbitofrontal, occipital, and cerebellar regions. Moreover, the patients with BD showed decreased rich club and feeder connectivity density. CONCLUSIONS Our results may reflect the disrupted white matter topological organization in the whole-brain, and abnormal regional connectivity supporting cognitive and affective functioning in depressed BD, which, in part, be due to impaired rich club connectivity.
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Affiliation(s)
- Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University,Guangzhou 510630,China
| | - Feng Deng
- Center for the Study of Applied Psychology & MRI Center, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Institute for Brain Research and Rehabilitation, South China Normal University,Guangzhou 510631,China
| | - Yanbin Jia
- Department of Psychiatry,First Affiliated Hospital of Jinan University,Guangzhou 510630,China
| | - Junjing Wang
- Center for the Study of Applied Psychology & MRI Center, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Institute for Brain Research and Rehabilitation, South China Normal University,Guangzhou 510631,China
| | - Shuming Zhong
- Department of Psychiatry,First Affiliated Hospital of Jinan University,Guangzhou 510630,China
| | - Huiyuan Huang
- Center for the Study of Applied Psychology & MRI Center, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Institute for Brain Research and Rehabilitation, South China Normal University,Guangzhou 510631,China
| | - Lixiang Chen
- Center for the Study of Applied Psychology & MRI Center, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Institute for Brain Research and Rehabilitation, South China Normal University,Guangzhou 510631,China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University,Guangzhou 510630,China
| | - Huiqing Hu
- Center for the Study of Applied Psychology & MRI Center, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Institute for Brain Research and Rehabilitation, South China Normal University,Guangzhou 510631,China
| | - Li Huang
- Medical Imaging Center, First Affiliated Hospital of Jinan University,Guangzhou 510630,China
| | - Ruiwang Huang
- Center for the Study of Applied Psychology & MRI Center, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Institute for Brain Research and Rehabilitation, South China Normal University,Guangzhou 510631,China
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Micro- and Macrostructural White Matter Integrity in Never-Treated and Currently Unmedicated Patients With Schizophrenia and Effects of Short-Term Antipsychotic Treatment. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2019; 4:462-471. [PMID: 30852126 DOI: 10.1016/j.bpsc.2019.01.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 12/17/2018] [Accepted: 01/08/2019] [Indexed: 01/26/2023]
Abstract
BACKGROUND Schizophrenia is associated with progressive white matter changes, but it is unclear whether antipsychotic medications contribute to these. Our objective was to characterize effects of short-term treatment with risperidone on white matter diffusion indices. METHODS We recruited 42 patients with schizophrenia (30 never treated and 12 currently untreated) and 42 matched healthy control subjects in this prospective case-control neuroimaging study. Patients received a 6-week trial of risperidone. Using diffusion tensor imaging, we assessed microstructural (fractional anisotropy, mean diffusivity, and radial diffusivity) and macrostructural (radial fiber trophy) white matter integrity deficits in unmedicated patients compared with control subjects and change in white matter integrity in patients before and after antipsychotic treatment (mean risperidone dose at end point was 3.73 ± 1.72 mg). RESULTS At baseline, fractional anisotropy was decreased in the left medial temporal white matter (cluster extent: 123 voxels; Montreal Neurological Institute peak coordinates: x = -51, y = -44, z = -7; α < .05), and mean diffusivity was increased in the fusiform/lingual gyrus white matter extending to the hippocampal part of the cingulum (cluster extent: 185 voxels; peak coordinates: x = -27, y = -49, z = 2; α < .04) in patients compared with control subjects. Radial diffusivity and macrostructure were not abnormal. None of the diffusion indices showed a significant change after 6 weeks of treatment with both voxelwise and whole-brain white matter analyses. CONCLUSIONS We demonstrate microstructural white matter integrity abnormalities in the absence of macrostructural impairment in unmedicated patients with primarily early-stage schizophrenia. In our data, we found no significant white matter changes after short-term treatment with risperidone.
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Tarcijonas G, Sarpal DK. Neuroimaging markers of antipsychotic treatment response in schizophrenia: An overview of magnetic resonance imaging studies. Neurobiol Dis 2018; 131:104209. [PMID: 29953933 DOI: 10.1016/j.nbd.2018.06.021] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 05/16/2018] [Accepted: 06/23/2018] [Indexed: 12/18/2022] Open
Abstract
Antipsychotic drugs are the primary treatment for psychosis, yet individual response to their administration remains variable. At present, no biological predictors of response exist to guide clinicians as they select treatments for patients, and our understanding of the neurobiology underlying the heterogeneity of outcomes remains limited. Magnetic Resonance Imaging (MRI) has been applied by numerous studies to examine the response to antipsychotic treatment, though a large gap remains between their results and our clinical practice. To advance patient care with precision medicine approaches, prior work must be accounted for and built upon with future studies. This review provides an overview of studies that relate treatment outcome to various MRI-related measures, including structural, spectroscopic, diffusion tensor, and functional imaging. Knowledge derived from these studies will be discussed along with future directions for the field.
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Affiliation(s)
- Goda Tarcijonas
- University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Deepak K Sarpal
- University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.
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Corpus callosum volumes in the 5 years following the first-episode of schizophrenia: Effects of antipsychotics, chronicity and maturation. NEUROIMAGE-CLINICAL 2018; 18:932-942. [PMID: 29876278 PMCID: PMC5988462 DOI: 10.1016/j.nicl.2018.03.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2017] [Revised: 02/19/2018] [Accepted: 03/14/2018] [Indexed: 01/27/2023]
Abstract
Background White matter (WM) structural changes, particularly affecting the corpus callosum (CC), seem to be critically implicated in psychosis. Whether such abnormalities are progressive or static is still a matter of debate in schizophrenia research. Aberrant maturation processes might also influence the longitudinal trajectory of age-related CC changes in schizophrenia patients. We investigated whether patients with first-episode schizophrenia-related psychoses (FESZ) would present longitudinal CC and whole WM volume changes over the 5 years after disease onset. Method Thirty-two FESZ patients and 34 controls recruited using a population-based design completed a 5-year assessment protocol, including structural MRI scanning at baseline and follow-up. The linear effects of disease duration, clinical outcome and antipsychotic (AP) use over time on WM and CC volumes were studied using both voxelwise and volume-based morphometry analyses. We also examined maturation/aging abnormalities through cross-sectional analyses of age-related trajectories of total WM and CC volume changes. Results No interaction between diagnosis and time was observed, and clinical outcome did not influence CC volumes in patients. On the other hand, FESZ patients continuously exposed to AP medication showed volume increase over time in posterior CC. Curve-estimation analyses revealed a different aging pattern in FESZ patients versus controls: while patients displayed a linear decline of total WM and anterior CC volumes with age, a non-linear trajectory of total WM and relative preservation of CC volumes were observed in controls. Conclusions Continuous AP exposure can influence CC morphology during the first years after schizophrenia onset. Schizophrenia is associated with an abnormal pattern of total WM and anterior CC aging during non-elderly adulthood, and this adds complexity to the discussion on the static or progressive nature of structural abnormalities in psychosis.
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Key Words
- AP, antipsychotics
- CC, corpus callosum
- Corpus callosum
- FEP, first episode of psychosis
- FESZ, First-episode of schizophrenia-related psychoses
- GM, gray matter
- MEM, mixed-effects model
- Magnetic resonance imaging
- Psychosis
- ROI, region-of-interest
- Schizophrenia
- VBM, voxel-based morphometry
- VolBM, volume-based morphometry
- WM, white matter
- White matter
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